metadata
language: en
tags:
- text-classification
pipeline_tag: text-classification
widget:
- text: >-
GEPS Techno is the pioneer of hybridization of renewable energies at sea.
We imagine, design and commercialize innovative off-grid systems that aim
to generate power at sea, stabilize and collect data. The success of our
low power platforms WAVEPEAL enabled us to scale-up the device up to
WAVEGEM, the 150-kW capacity platform.
Environmental Impact (CODE CARBON DEFAULT)
Metric | Value |
---|---|
Duration (in seconds) | 69774.12664532661 |
Emissions (Co2eq in kg) | 0.0422214063591651 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 0.8237207426448668 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.0726807426561913 |
Consumed energy (kWh) | 0.8964014853010585 |
Country name | Switzerland |
Cloud provider | nan |
Cloud region | nan |
CPU count | 2 |
CPU model | Intel(R) Xeon(R) Platinum 8360Y CPU @ 2.40GHz |
GPU count | nan |
GPU model | nan |
Environmental Impact (for one core)
Metric | Value |
---|---|
CPU energy (kWh) | 0.13431519379225373 |
Emissions (Co2eq in kg) | 0.02732819960275292 |
Note
19 juin 2024
My Config
Config | Value |
---|---|
checkpoint | albert-base-v2 |
model_name | ft_16_10e6_base_x12 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 1e-05 |
batch_size | 16 |
weight_decay | 0.0 |
warm_up_prop | 0.0 |
drop_out_prob | 0.1 |
packing_length | 100 |
train_test_split | 0.2 |
num_steps | 29328 |
Training and Testing steps
Epoch | Train Loss | Test Loss | F-beta Score |
---|---|---|---|
0 | 0.000000 | 0.714335 | 0.597948 |
1 | 0.347528 | 0.296561 | 0.929597 |
2 | 0.226067 | 0.231189 | 0.900926 |
3 | 0.186524 | 0.249437 | 0.918742 |
4 | 0.152025 | 0.236880 | 0.922707 |
5 | 0.125592 | 0.257051 | 0.932766 |
6 | 0.091767 | 0.295228 | 0.902097 |